Field of the Invention
Embodiments of the present invention relate generally to pricing engines, and more particularly to travel, or cargo shipment pricing engines.
Discussion of the Related Art
Conventionally, various systems have existed for analyzing travel or cargo fares data and fare-related data. One example environment may include air passenger fare and fare related data. Fare and fare related data may include, e.g., but is not limited to, fares, fare restriction data, routing restriction data, currency conversion rate data, schedule data, tax data, facility charge data, geographic information, and ancillary data. Such air passenger fare and fare related data is published and available on a subscription basis from Airline Tariff Publishing Company (ATPCO) of Dulles, Va., USA, assignee of the present invention. A portion of the disclosure of this patent document contains material to which a claim for copyright is made. Various copyrighted materials may be included herein, with annotation ©ATPCO 2013, and ATPCO reserves its rights in such copyrighted subject matter. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but reserves all other copyright rights whatsoever.
A conventional pricing system may be used to produce one or more itineraries and prices by selecting suitable travel units from databases containing geographic, scheduling and/or pricing information. In the airline industry, for example, fundamental travel units may include “flights” (sequences of regularly scheduled takeoffs and landings assigned a common identifier) and “fares” (prices published by airlines for travel between two points). The term “itinerary” may refer to a sequence of flights on particular dates and the term “pricing solution” may refer to a combination of fares and itineraries.
A pricing query may typically include, e.g., an origin (O), a destination (D), time constraints, and may include additional information such as, e.g., but not limited to, a passenger profile and/or travel preferences. A pricing system may respond to a pricing query and may return a list of one or more possible itineraries including a combination of a flight with a price.
A pricing system may expend considerable computing resources responding to a pricing query. It is not uncommon for a pricing system to spend more than 30 seconds responding to an pricing query, even for a relatively straightforward round-trip query departing and returning from a specific airport on a specific date. Any delay may be undesirable for a user of the system.
Pricing Systems may use specialized techniques to review fare offerings, whether published or unpublished (i.e., specially offered fares not normally available), across a number of different vendors (including, e.g., airline, hotel, or car rental companies, etc.) and may return results to a user in a ranked order based on one or more parameters or attributes a customer has requested, such as, e.g., but not limited to, by price, etc. Each vendor's computer system may allow fare search engines to determine which of the vendor's fares are available for a given date and itinerary being considered, and fare search engines may sort and select best alternatives in response to a query. The objective of traditional fare search processing is to find the best fare offers available in a relevant marketplace.
The processing of example air travel related pricing requests is a difficult problem to solve efficiently and requires simultaneous scrutiny of many factors that span, e.g., but not limited to, flight schedules, availability, published fares, rule restrictions, complex business logic, and carrier exceptions, etc. The order in which variables are analyzed has evolved with varying degrees of success while continuously emphasizing the need for more efficient techniques for processing requests.
The vast array of fares and fare related rules business data presents a data processing challenge. Conventional systems emphasize a sequence of origination destination pairs formed from schedules or fares. Large volumes of such travel and/or cargo fare and fare related data that must be directly accessed, cross-referenced, or traversed in processing a database query to process a specific transaction presents a substantial data processing challenge.
It would therefore be advantageous to provide improved techniques to more efficiently process travel, cargo, and the like, pricing requests.
Conventional pricing system methods and systems have various shortcomings. What is needed is an improved system and method that overcomes the various shortcomings of conventional solutions.